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Updated: Apr 10, 2026

An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
[Application of spatial relative risk estimation in communicable disease risk evaluation]
Yewu Zhang1, Qing Guo1, Xiaofeng Wang1
1Center for Disease Surveillance and Information Services, Chinese Center for Disease Control and Prevention, Beijing 102206, China.
Abstract:
This paper summaries the application of adaptive kernel density algorithm in the spatial relative risk estimation of communicable diseases by using the reported data of infectious diarrhea (other than cholera, dysentery, typhoid and paratyphoid) in Ludian county and surrounding area in Yunnan province in 2013. Statistically significant fluctuations in an estimated risk function were identified through the use of asymptotic tolerance contours, and finally these data were visualized though disease mapping. The results of spatial relative risk estimation and disease mapping showed that high risk areas were in southeastern Shaoyang next to Ludian. Therefore, the spatial relative risk estimation of disease by using adaptive kernel density algorithm and disease mapping technique is a powerful method in identifying high risk population and areas.
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